摘要
【目的】探索高邮灌区的参考作物腾发量(ET_(0))预报方法,提升灌溉预报精度。【方法】基于高邮灌区2003—2017年实测气象数据及2016—2017年气温预报数据,以FAO-56 Penman-Monteith(PM)计算的ET_(0)为基准,将气温预报数据代入率定后的Blaney-Criddle(BC)、Hargreaves-Samani(HS)、McCloud(MC)和简化的PM(PMT)模型,比较不同模型的ET_(0)预报精度。【结果】基于上述4种模型进行ET_(0)预报时,1~7 d预见期的平均均方根误差分别为1.07、1.00、1.16、0.99 mm/d,绝对误差平均值分别为0.85、0.74、0.94、0.75 mm/d,相关系数平均值分别为0.79、0.81、0.76、0.81。【结论】HS和PMT模型的预报精度最好,优于BC和MC模型,MC模型的预报精度最差。建议采用率定后的HS和PMT模型对高邮灌区ET_(0)进行预报。
【Objective】Gaoyou irrigation district is located at the low reaches of the Yangtze River in northern Jiangsu province,China.To improve its irrigation management,we compared four models for predicting the reference evapotranspiration(ET_(0))in the district.【Method】The analysis was based on meteorological data measured from 2003 to 2017 and the temperature forecasted from 2016 to 2017 in the district,from which we calculated the ET_(0) using the Penman-Monteith(PM)formula recommended by FAO-56.Using these calculated ET_(0),we forecasted its change using the Blaney-Criddle(BC),Hargreaves-Samani(HS),McCloud(MC)and reduced PM(PMT)model,respectively.【Result】For forecasting ET_(0)1 to 7 days in advance,the average root mean square error of the BC,HS,MC and PMP model was 1.07,1.00,1.16,0.99 mm/d,respectively;their associated average mean absolute error was 0.85,0.74,0.94,0.75 mm/d,respectively;their associated average correlation coefficient with measured data was 0.79,0.81,0.76,0.81,respectively.Overall,the results of HS and PMT model are comparable and both models are superior to other models for forecasting the ET_(0) up to 7 days in advance.【Conclusion】Among the four models we compared,the HS and PMT models are more accurate for predicting ET_(0) change 1-7 days in advance for the Gaoyou irrigation district.
作者
刘梦
仇锦先
张秝湲
王洁
丁奠元
刘博
LIU Meng;QIU Jinxian;ZHANG Liyuan;WANG Jie;DING Dianyuan;LIU Bo(Yangzhou Survey,Design and Research Institute Co.Ltd,Yangzhou 225002,China;College of Hydraulic Science and Engineering,Yangzhou University,Yangzhou 225009,China;Water Resources Service Center of Jiangsu Province,Nanjing 210029,China;Yangzhou Water Conservancy Bureau,Yangzhou 225009,China)
出处
《灌溉排水学报》
CAS
CSCD
2024年第4期28-33,49,共7页
Journal of Irrigation and Drainage
基金
国家自然科学基金(52079119)
江苏省水利厅科技合作项目(JSZC-320000-HYGS-C2023-00472)
江苏省高等学校基础科学研究面上项目(21KJB210021)。
关键词
参考作物腾发量
气温预报
灌溉
reference evapotranspiration
temperature forecast
irrigation
